“This paper presents an assessment of the potential impact of the EUs biofuel directive on European land use and biodiversity. In a spatially explicit analysis, it is determined which ecologically valuable land use types are likely to be directly replaced by biofuel crops. In addition, it is determined which land use types may be indirectly replaced by biofuel crops through competition over land between biofuel and food crops. Four scenarios of land use change are analyzed for the period 2000-2030 while for each scenario two policy variants are analyzed respectively with and without implementation of the biofuel directive. The results indicate that the area of semi natural vegetation, forest and High Nature Value farmland directly replaced by biofuel crops is small in all scenarios and differs little between policy variants. The direct effects of the directive on European land use and biodiversity therefore are relatively minor. The indirect effects of the directive on European land use and biodiversity are much larger than its direct effects. The area semi natural vegetation is found to be 3-8% smaller in policy variants with the directive as compared to policy variants without the directive. In contrast, little difference is found between the policy variants with respect to the forest area. The results of this study show that the expected indirect effects of the directive on biodiversity are much greater than its direct effects. This suggests that indirect effects need to be taken explicitly into account in assessing the environmental effects of biofuel crop cultivation and designing sustainable pathways for implementing biofuel policies.”

“The Winston-Salem State University “Transforming Communities Research Lab” at the Center for Community Safety is a practical, community-based research engine to inform community and agency decision-making and a means through which individuals can glean and use information in ways that enhance their knowledge and power. GIS is at the heart of this endeavor. TCRL has provided “basic training” in using GIS to students, faculty staff. TCRL is making these tools available to the public and sharing them with human service and community development agencies, which fulfills one of CCS’s original goals to be a local resource center for community safety. One of the (if not the only) full service GIS labs that is available to not only students and faculty, TCRL is made available to every segment of the community to utilize the power of GIS in their own ways. TCRL has developed free workshops for learning the basics of GIS. Students from WSSU, WFU, Salem College, Forsyth Technical Community College, Elon University and UNCG have come to enhance their normal curriculum with GIS. Neighborhood Associations, Faith Based Organizations and other community leadership organizations have attended workshops. Community agencies such as school system social workers, city and county government personnel have also attended our workshops. TCRL invites people to learn what GIS is and experience hands on learning with ArcGIS software. After each workshop, they are invited to come back and use the software and the over 900 layers of data that is available. With TCRL staff assistance, they are taught to use GIS to use their research strategically to shape action and response to community safety issues. Our definition of community safety is a very holistic approach. As a result, we try to develop crime, demographic, infrastructure, business and environmental data to help accomplish this endeavor. This paper and presentation details the TCRL history and gives examples of participant works in community prisoner re-entry, crime analysis, health disparity, health sciences windshield surveys, community historic preservation, neighborhood & community communication and non-profit funding applications. It is important to note that even if a workshop participant does not come back to utilize the software at TCRL, the staff are available by phone and e-mail to assist with their data needs and other services. The participant may now go to a planning board or other public forum where maps and data are presented and they will know how to ask questions of the data presented or be able to ascertain what is actually being communicated.”

“GIS is increasingly used in poverty mapping but there is no generic data model for database development. Examples exist already of industry-specific models. Having such a data model eases the complexity of incorporating spatial data in poverty assessments. This article raises awareness about the need for a generic poverty data model for use in poverty mapping. It seeks to stimulate a lively debate that will lead to the development and adoption of such a data model. The ultimate goal will be to get to some level of standardization for common data types that would facilitate spatial data use in poverty assessment and sharing among poverty projects. This article is a first step at developing a data model for poverty mapping at a conceptual level. Handling multidimensional social problems, such as poverty, using a spatial framework can be challenging because of the myriad of poverty indicators in use. Employing the entity-relationship approach, a conceptual model is developed in the current article that identifies the key thematic layers, entities, and relationships. The conceptual model produced is useful for modeling the content of the database for use in assessing and monitoring poverty.”

Journal of the American Statistical Association, June 1, 2010, 105(490): 538-551

Sujit K. Ghosh, Prakash V. Bhave, Jerry M. Davis, and Hyeyoung Lee

“Atmospheric concentrations of total nitrate (TNO3), defined here as gas-phase nitric acid plus particle-phase nitrate, are difficult to simulate in numerical air quality models due to the presence of a variety of formation pathways and loss mechanisms, some of which are highly uncertain. The goal of this study is to estimate the relative importance of these different pathways across the Eastern United States by identifying empirical relationships that exist between TNO3 concentrations and a set of covariates (ammonium, sulfate, ozone, wind speed, relative humidity, and precipitation) measured from January 1997 to July 2004. We develop two dynamic statistical models to quantify these relationships. A major advantage of these models over typical linear regression models is that their regression coefficients can vary temporally. Results show that TNO3 is sensitive to ozone throughout the year, indicating an importance of daytime photochemical production of TNO3, especially in the Southeast. Sensitivity of TNO3 to residual ammonium (NH4+–2SO42−) is most pronounced during winter, indicating a seasonal importance of gas/particle partitioning that is accentuated in the Midwest. Using a number of physical and chemical explanations, confidence is established in the spatial and temporal patterns of several such empirical relationships. In the future, these relationships may be used quantitatively to improve our mechanistic understanding of TNO3 formation pathways and loss mechanisms in the atmosphere.”

“To evaluate the frequency and distribution of landslides hazards over Japan, this study uses a probabilistic model based on multiple logistic regression analysis. Study particular concerns several important physical parameters such as hydraulic parameters, geographical parameters and the geological parameters which are considered to be influential in the occurrence of landslides. Sensitivity analysis confirmed that hydrological parameter (hydraulic gradient) is the most influential factor in the occurrence of landslides. Therefore, the hydraulic gradient is used as the main hydraulic parameter; dynamic factor which includes the effect of heavy rainfall and their return period. Using the constructed spatial data-sets, a multiple logistic regression model is applied and landslide hazard probability maps are produced showing the spatial-temporal distribution of landslide hazard probability over Japan. To represent the landslide hazard in different temporal scales, extreme precipitation in 5 years, 30 years, and 100 years return periods are used for the evaluation. The results show that the highest landslide hazard probability exists in the mountain ranges on the western side of Japan (Japan Sea side), including the Hida and Kiso, Iide and the Asahi mountainous range, the south side of Chugoku mountainous range, the south side of Kyusu mountainous and the Dewa mountainous range and the Hokuriku region. The developed landslide hazard probability maps in this study will assist authorities, policy makers and decision makers, who are responsible for infrastructural planning and development, as they can identify landslide-susceptible areas and thus decrease landslide damage through proper preparation.”

“Coal power generation in China and India could double and triple, respectively, over the next 20 years, which would increase exposure to fuel price volatility, exacerbate local air pollution, and hasten global climate change. Moving to concentrating solar power (CSP), a growing source of utility-scale, pollution-free electricity, would help alleviate these problems, but its potential in Asia remains largely unexamined. In this working paper, Kevin Ummel uses high-resolution spatial data to identify areas suitable for CSP and estimates power generation and cost under various land-use scenarios.

“Total CSP potential in China is at least 16 times greater than current coal power output; in India, it is at least 3 times greater. A CSP expansion program could provide 20 percent of electricity in both countries by midcentury. Under conservative assumptions, the program will require subsidies of $340 billion in present dollars. Estimated costs are especially sensitive to the assumed rate of technological learning, making it especially important to form committed public policy and financing to reduce investment risk, encourage the expansion of manufacturing capacity, and achieve long-term cost reductions.”